In the following experiments, the proposed Ms-CapsNet is compared with four closely related methods, including the PCANet [1]}, the transferred multilevel fusion network (MLFN) [2]}, the deep convolutional neural networks (DCNN) [3]}, and the CNN with local spatial restrictions (LR-CNN) [4]}. To verify the effectiveness of the proposed Ms-CapsNet, false positives (FP), false negatives (FN), percentage correct classification (PCC), overall errors (OE), and Kappa coefficient (KC) are adopted as the evaluation criteria.
